46 research outputs found
Fine-Grained Static Detection of Obfuscation Transforms Using Ensemble-Learning and Semantic Reasoning
International audienceThe ability to efficiently detect the software protections used is at a prime to facilitate the selection and application of adequate deob-fuscation techniques. We present a novel approach that combines semantic reasoning techniques with ensemble learning classification for the purpose of providing a static detection framework for obfuscation transformations. By contrast to existing work, we provide a methodology that can detect multiple layers of obfuscation, without depending on knowledge of the underlying functionality of the training-set used. We also extend our work to detect constructions of obfuscation transformations, thus providing a fine-grained methodology. To that end, we provide several studies for the best practices of the use of machine learning techniques for a scalable and efficient model. According to our experimental results and evaluations on obfuscators such as Tigress and OLLVM, our models have up to 91% accuracy on state-of-the-art obfuscation transformations. Our overall accuracies for their constructions are up to 100%
Certificateless Proxy Signature from RSA
Although some good results were achieved in speeding up the computation of pairing function in recent years, it is still interesting to design efficient cryptosystems with less bilinear pairing operation. A proxy signature scheme allows a proxy signer to sign messages on behalf of an original signer within a given context. We propose a certificateless proxy signature (CLPS) scheme from RSA and prove its security under the strongest security model where the Type I/II adversary is a super Type I/II adversary
The Role of the Adversary Model in Applied Security Research
Adversary models have been integral to the design of provably-secure cryptographic schemes or protocols. However, their use in other computer science research disciplines is relatively limited, particularly in the case of applied security research (e.g., mobile app and vulnerability studies). In this study, we conduct a survey of prominent adversary models used in the seminal field of cryptography, and more recent mobile and Internet of Things (IoT) research. Motivated by the findings from the cryptography survey, we propose a classification scheme for common app-based adversaries used in mobile security research, and classify key papers using the proposed scheme. Finally, we discuss recent work involving adversary models in the contemporary research field of IoT. We contribute recommendations to aid researchers working in applied (IoT) security based upon our findings from the mobile and cryptography literature. The key recommendation is for authors to clearly define adversary goals, assumptions and capabilities
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http://www.ester.ee/record=b4338625~S1*es
A Touch of Evil: High-Assurance Cryptographic Hardware from Untrusted Components
The semiconductor industry is fully globalized and integrated circuits (ICs)
are commonly defined, designed and fabricated in different premises across the
world. This reduces production costs, but also exposes ICs to supply chain
attacks, where insiders introduce malicious circuitry into the final products.
Additionally, despite extensive post-fabrication testing, it is not uncommon
for ICs with subtle fabrication errors to make it into production systems.
While many systems may be able to tolerate a few byzantine components, this is
not the case for cryptographic hardware, storing and computing on confidential
data. For this reason, many error and backdoor detection techniques have been
proposed over the years. So far all attempts have been either quickly
circumvented, or come with unrealistically high manufacturing costs and
complexity.
This paper proposes Myst, a practical high-assurance architecture, that uses
commercial off-the-shelf (COTS) hardware, and provides strong security
guarantees, even in the presence of multiple malicious or faulty components.
The key idea is to combine protective-redundancy with modern threshold
cryptographic techniques to build a system tolerant to hardware trojans and
errors. To evaluate our design, we build a Hardware Security Module that
provides the highest level of assurance possible with COTS components.
Specifically, we employ more than a hundred COTS secure crypto-coprocessors,
verified to FIPS140-2 Level 4 tamper-resistance standards, and use them to
realize high-confidentiality random number generation, key derivation, public
key decryption and signing. Our experiments show a reasonable computational
overhead (less than 1% for both Decryption and Signing) and an exponential
increase in backdoor-tolerance as more ICs are added